Rate control is a critical issue in H.264/AVC video coding standard because it suffers from some shortcomings that make the bit allocation process not optimal. This leads to a video quality that may vary significantly from frame to frame. Our aim is to enhance the rate control efficiency in H.264/AVC baseline profile by handling two of its defects: the initial quantization parameter (QP) estimation for Intra-Frames (I-Frames) and the target number of bits determination for Inter-Frames (P-Frames) encoding. First, we propose a Rate-Quantization (R-Q) model for the I-Frame constructed empirically after extensive experiments. The optimal initial QP calculation is based on both target bit-rate and I-Frame complexity. The I-Frame target bit-rate is derived from the global target bit-rate by using a new non-linear model. Secondly, we propose an enhancement of the bit allocation process by exploiting frame complexity measures. The target number of bits determination for P-Frames is adjusted by combining two temporal measures: the first is a motion ratio based on actual bits used to encode previous frames; the second measure exploits the difference between two consecutive frames and the histogram of this difference. The simulation results, carried out using the JM15.0 reference software and the JVT-O016 rate control algorithm, show that the right choice of initial QP for I-Frame and first P-Frame allows improvement of both the bit-rate and peak signal-to-noise ratio (PSNR). Finally, the Inter-Frame bit allocation process further improves the bit-rates while keeping the same PSNR improvement (up to +1.33 dB/+2 dB for QCIF/CIF resolutions). Moreover, this process reduces the buffer level variation leading to a more consistent quality of reconstructed videos.
In H.264/AVC rate control algorithm, the bit allocation process and the QP determination are not optimal.
At frame layer, there is an implicit assumption considering that the video sequence is more or less stationary
and consequently the neighbouring frames have similar characteristics. So, the target Bit-Rate for each frame
is estimated using a straightforward process that allocates an equal bit budget for each frame regardless of its
temporal and spatial complexities. This uniform allocation is surely not suited especially for all types of video
sequences. The target bits determination at macroblock layer uses the MAD (Mean Absolute Difference) ratio
as a complexity measure in order to promote interesting macroblocks, but this measure remains inefficient in
handling macroblock characteristics. In a previous work we have proposed Rate-Quantization (R-Q) models
for Intra and Inter frames used to deal with the QP determination shortcoming. In this paper, we look to
overcome the limitation of the bit allocation process at the frame and the macroblock layers. At the frame
level, we enhance the bit allocation process by exploiting frame complexity measures. Thereby, the target bit
determination for P-frames is adjusted by combining two temporal measures: The first one is a motion ratio
determined from actual bits used to encode previous frames. The second measure exploits both the difference
between two consecutive frames and the histogram of this difference. At macroblock level, the visual saliency
is used in the bit allocation process. The basic idea is to promote salient macroblocks. Hence, a saliency map,
based on a Bottom-Up approach, is generated and a macroblock classification is performed. This classification
is then used to accurately adjust UBits<sub>H264</sub> which represents the usual bit budget estimated by H.264/AVC
bit allocation process. For salient macroblocks the adjustment leads to a bit budget which is always larger
than UBits<sub>H264</sub>. The extra bits added to code these macroblocks are deducted from the bit budget allocated
to the non-salient macroblocks. Simulations have been carried out using JM15.0 reference software, several
video sequences and different target Bit-Rates. In comparison with JM15.0 algorithm, the proposed approach
improves the coding efficiency in terms of PSNR/PSNR-HVS (up to +2dB/+3dB). Furthermore, the bandwidth
constraint is always satisfied because the actual Bit-Rate is always lower than or equal to the target Bit-Rate.
Rate control plays a key role in video coding standards. Its goal is to achieve a good quality at a given target
bit-rate. In H.264/AVC, rate control algorithm for both Intra and Inter-frames suffers from some defects. In
the Intra-frame rate control, the initial quantization parameter (QP) is mainly adjusted according to a global
target bit-rate and length of GOP. This determination is inappropriate and generates errors in the whole of
video sequence. For Inter coding unit (Frame or Macroblock), the use of MAD (Mean Average Differences) as
a complexity measure, remains inefficient, resulting in improper QP values because the MAD handles locally
images characteristics. QP miscalculations may also result from the linear prediction model which assumes
similar complexity from coding unit to another. To overcome these defects, we propose in this paper, a new
Rate-Quantization (R-Q) model resulting from extensive experiments. This latter is divided into two models.
The first one is an Intra R-Q model used to determine an optimal initial quantization parameter for Intraframes.
The second one is an Inter R-Q model that aims at determining the QP of Inter coding unit according
to the statistics of the previous coded ones. It does not use any complexity measure and substitutes both
linear and quadratic models used in H.264/AVC rate controller. Objective and subjective simulations have been
carried out using JM15.0 reference software. Compared to this latter, the global R-Q model (Intra and Inter
models combined) improves the coding efficiency in terms of PSNR, objectively (up to +2.01dB), subjectively
(by psychophysical experiments) and in terms of computational complexity.